Hello;

I am using DESeq2 for DEG discovery, however I found changes in p-adjust value depending the alpha I used in the same gene. For example using the default alpha value (0.1) for results I got:

res05 <- results(ddi, contrast=c("treatmenttissue",conditionsName[2],conditionsName[6])) res05Ordered <- res05[order(res05$pvalue),] data05 <- na.omit(as.data.frame(res05Ordered)) keepAllDEgenes <- (data05$padj<=0.05) genesDE<-data05[keepAllDEgenes,] genesDE["TRINITYDN64996c0g2",] baseMean log2FoldChange lfcSE stat pvalue TRINITYDN64996c0g2 31.79655 -1.443795 0.4637561 -3.113262 0.001850314 padj TRINITYDN64996c0g2 0.04894679

But if I change to alpha=0.05

res05 <- results(ddi, contrast=c("treatmenttissue",conditionsName[2],conditionsName[6]),alpha=0.05) res05Ordered <- res05[order(res05$pvalue),] data05 <- na.omit(as.data.frame(res05Ordered)) data05["TRINITYDN64996c0g2",] baseMean log2FoldChange lfcSE stat pvalue TRINITYDN64996c0g2 31.79655 -1.443795 0.4637561 -3.113262 0.001850314 padj TRINITYDN64996c0g2 0.2324749

No my gene is not significan differential expressed in means of p-adjust values. This become annoying beacause if now I did a cut-off alpha of 0.01

res05 <- results(ddi, contrast=c("treatmenttissue",conditionsName[2],conditionsName[6]),alpha=0.01) res05Ordered <- res05[order(res05$pvalue),] data05 <- na.omit(as.data.frame(res05Ordered)) data05["TRINITYDN64996c0g2",] baseMean log2FoldChange lfcSE stat pvalue TRINITYDN64996c0g2 31.79655 -1.443795 0.4637561 -3.113262 0.001850314 padj TRINITYDN64996c0g2 0.0378142

This same gene become a DEG. My question is why do the padjust value changes drastically depending an alpha value?, and if so why 0.05 is worst than 0.01 in means of p-value tests.

I hope you can answer.

Best

Arturo.

Yes, if you read the help page for ?results, you will see that alpha changes the target for the independent filtering procedure, therefore producing different adjusted p-values. See also the Independent Filtering section of the vignette.